The Molecular Interaction Process

Laue, Thomas M.; Shire, Steven J.

doi:10.1016/j.xphs.2019.10.045

Cited by 16 publications

(9 citation statements)

References 96 publications

(187 reference statements)

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“…The sedimenting particle has an effective solvated volume V s that reflects hydration, shape through an f/f o term, and the entrained solvent captured within the Debye length (Fuoss 1959;Fuoss and Onsager 1932;Rowe 1977Rowe , 1992. It is worth noting that the effective charge is much smaller than typically assumed due to charge screening and anion binding (Laue 2011;Laue and Shire 2020). This in principle reflects the Stokes radius of the effective electroneutral sphere.…”

Section: Discussionmentioning

confidence: 98%

Analysis of nonideality: insights from high concentration simulations of sedimentation velocity data

et al. 2020

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The Aviv fluorescence detection system (Aviv-FDS) has allowed the performance of sedimentation velocity experiments on therapeutic antibodies in highly concentrated environments like formulation buffers and serum. Methods were implemented in the software package SEDANAL for the analysis of nonideal, weakly associating AUC data acquired on therapeutic antibodies and proteins (Wright et al. Eur Biophys J 47:709–722, 2018, Anal Biochem 550:72–83, 2018). This involved fitting both hydrodynamic, ks, and thermodynamic, BM1, nonideality where concentration dependence is expressed as s = so/(1 + ksc) and D = Do(1 + 2BM1c)/(1 + ksc) and so and Do are values extrapolated to c = 0 (mg/ml). To gain insight into the consequences of these phenomenological parameters, we performed simulations with SEDANAL of a monoclonal antibody as a function of ks (0–100 ml/g) and BM1 (0–100 ml/g). This provides a visual understanding of the separate and joint impact of ks and BM1 on the shape of high-concentration sedimentation velocity boundaries and the challenge of their unique determination by finite element methods. In addition, mAbs undergo weak self- and hetero-association (Yang et al. Prot Sci 27:1334–1348, 2018) and thus we have simulated examples of nonideal weak association over a wide range of concentrations (1–120 mg/ml). Here we demonstrate these data are best analyzed by direct boundary global fitting to models that account for ks, BM1 and weak association. Because a typical clinical dose of mAb is 50–200 mg/ml, these results have relevance for biophysical understanding of concentrated therapeutic proteins.

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Section: Discussionmentioning

confidence: 98%

Analysis of nonideality: insights from high concentration simulations of sedimentation velocity data

et al. 2020

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“…For antibody therapeutics, the isoelectric point (pI, the pH at which the molecule is neutral) is a key measure of developability since a pI near the formulation pH may lead to high viscosity and aggregation or precipitation. [61][62][63][64] A slightly acidic pH generally results in a higher overall charge leading to more recent formulations centered around pH 5.5. 65 To remain stable in solution, therapeutic antibodies would ideally need to have a pI of greater than 8.5 for the overall molecule.…”

Section: Figure 2 Bias and Control Of Antibody-gan Library Features Umentioning

confidence: 99%

Designing Feature-Controlled Humanoid Antibody Discovery Libraries Using Generative Adversarial Networks

Amimeur

Shaver

Ketchem

et al. 2020

Preprint

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We demonstrate the use of a Generative Adversarial Network (GAN), trained from a set of over 400,000 light and heavy chain human antibody sequences, to learn the rules of human antibody formation. The resulting model surpasses common in silico techniques by capturing residue diversity throughout the variable region, and is capable of generating extremely large, diverse libraries of novel antibodies that mimic somatically hypermutated human repertoire response. This method permits us to rationally design de novo humanoid antibody libraries with explicit control over various properties of our discovery library. Through transfer learning, we are able to bias the GAN to generate molecules with key properties of interest such as improved stability and developability, lower predicted MHC Class II binding, and specific complementarity-determining region (CDR) characteristics. These approaches also provide a mechanism to better study the complex relationships between antibody sequence and molecular behavior, both in vitro and in vivo . We validate our method by successfully expressing a proof-of-concept library of nearly 100,000 GAN-generated antibodies via phage display. We present the sequences and homology-model structures of example generated antibodies expressed in stable CHO pools and evaluated across multiple biophysical properties. The creation of discovery libraries using our in silico approach allows for the control of pharmaceutical properties such that these therapeutic antibodies can provide a more rapid and cost-effective response to biological threats.

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“…3 High concentration protein solutions often experience "crowded" environments in solution, 13 forming a network of reversible protein-protein interactions (PPIs), or self-associations, leading to increased solution viscosity. [14][15][16] In addition, elevated solution viscosity can lead to high shear stress during pumping/ filling, potentially leading to protein denaturation, 3,17 as well as filter membrane clogging during filtration in the manufacturing process. 18,19 Such manufacturing challenges have been assumed to be alleviated by lowering solution viscosity.…”

Section: Introductionmentioning

confidence: 99%

Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development

Rodrigues

Tanenbaum

Thirumangalathu

et al. 2021

Journal of Pharmaceutical Sciences

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The Molecular Interaction Process

Cited by 16 publications

References 96 publications

Analysis of nonideality: insights from high concentration simulations of sedimentation velocity data

Analysis of nonideality: insights from high concentration simulations of sedimentation velocity data

Designing Feature-Controlled Humanoid Antibody Discovery Libraries Using Generative Adversarial Networks

Product-Specific Impact of Viscosity Modulating Formulation Excipients During Ultra-High Concentration Biotherapeutics Drug Product Development

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